"Evolving Genetic Regulatory Networks Performing as Oscillators and Switches in the Stochastic Regime"

Dr. André Leier

University of Queensland, Australia

Recent studies have shown that small genetic regulatory networks (GRNs) can
be evolved in silico displaying certain dynamics in the underlying
mathematical model. To take the stochastic nature of GRNs into account, our
evolutionary approach models GRNs as biochemical reaction networks based on
simple enzyme kinetics and simulates them by using Gillespie's stochastic
simulation algorithm (SSA). The relevance of considering intrinsic
stochasticity is demonstrated by GRNs which show certain dynamics in the SSA
but not in the ODE regime. First results in the evolution of GRNs performing
as stochastic oscillators and switches are presented. It is expected that
evolutionary approaches can help to gain a better understanding of
biological design principles and to assist in synthetic biology.